Systems-oriented ML/LLM Engineer

Systems-oriented ML/LLM engineer using Python/PyTorch and Rust for low-latency/high throughput services. Has a PhD in mathematics (statistical methods/modeling, topological data analysis, representation theory) and master's theses in finance and neuroscience. Expertise includes applications of machine learning/deep learning to banking/finance for risk evaluation and fraud prediction, and LLMs and agentic frameworks (tools, planning, evaluation). Rust focus on async services (Tokio, Axum/Actix), data/compute (Polars/Arrow), production systems and performance-critical pipelines. Has worked across domains such as banking/finance, domain-specific image analysis, neuroscience, audio processing, and low-level database optimizations. Actively exploring remote opportunities where they can apply their combination of math and developer skills to interesting challenges. Open to freelance/contract work (can invoice via own company) or full-time. Open to US work.